Ursa

Ursa performs automated analysis of single-cell multiomics and spatial transcriptomics data to integrate genomics, transcriptomics, epigenetics, proteomics, and immunomics and to support dimension reduction, clustering, pseudotime trajectory, and gene-set enrichment analyses.

Key Features:

• Automated Workflows: Provides six automated workflows tailored for single-cell omics and spatial transcriptomics analyses.
• Multi-Omics Integration: Integrates genomics, transcriptomics, epigenetics, proteomics, and immunomics data for joint analysis.
• Quality Control and Assessment: Implements quality control assessments as part of the analytical pipeline.
• Multidimensional Analyses: Performs dimension reduction and clustering to reveal structure in complex single-cell datasets.
• Extended Analytical Functions: Includes pseudotime trajectory analysis and gene-set enrichment analyses for dynamic and functional investigations.

Scientific Applications:

• Cancer Research: Analyzes tumor microenvironments at single-cell resolution to identify biomarkers and cellular interactions.
• Developmental Biology: Investigates cell lineage trajectories and differentiation pathways during organismal development.
• Immunology: Profiles immune cell populations and responses at high resolution to study disease mechanisms and vaccine responses.

Methodology:

Implemented in the R programming language with a modular, extensible framework providing six automated workflows for single-cell omics and spatial transcriptomics analyses.